在DOM中恢复异常水面 无人机遥感的产品,使用本地图像替换
Chunjie Wang1, Ti Zhang2, Liang Tao3
1Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China.
Sensors (Basel, Switzerland)
|July 12, 2025
概括
本研究介绍了一种方法来修复从无人机图像创建的数字正视图地图 (DOM) 中的水面异常. 通过将有缺陷的水域替换为来自单一图像的完整水域,DOM的视觉质量和数据完整性得到了显著改善.
科学领域:
- 摄影测量和遥感技术的应用
- 地理空间数据处理.
- 计算机视觉 计算机视觉
背景情况:
- 来自无人机 (UAV) 图像的数字正形图 (DOM) 经常显示出水域的异常,原因是纹理有限.
- 这些异常,如纹理拉伸和数据漏洞,降低了DOM的视觉质量和数据完整性.
研究的目的:
- 开发和验证一种方法,以消除基于无人机的DOM中的水面异常.
- 通过恢复有问题的水域,提高DOM的视觉质量和数据完整性.
主要方法:
- 使用多源种子填充和轮查找算法精确识别水面范围和边界.
- 从正常和异常水界选择的结合点,通过亲属转换进行空间对齐.
- 从单个无人机图像中提取的完整水域取代了DOM中的异常水面.
主要成果:
- 恢复后的水域表现出了出色的光谱一致性和与周围环境的自然纹理过渡.
- 定量分析显示,DOM质量显著改善,以减少标准偏差和改变RGB像素的平均值为准.
- 该方法有效地恢复了异常的水面,特别是在DOM中,小型水体包含在单个无人机图像中.
结论:
- 提出的方法成功地消除了无人机衍生的DOM中的水面异常.
- 该技术提高了最终的正视图地图的视觉吸引力和数据完整性.
- 这种方法为改善DOM质量在具有挑战性的水特征的地区提供了实际解决方案.
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